本文整理汇总了Python中scipy.spatial.Delaunay.sum方法的典型用法代码示例。如果您正苦于以下问题：Python Delaunay.sum方法的具体用法？Python Delaunay.sum怎么用？Python Delaunay.sum使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类scipy.spatial.Delaunay的用法示例。
在下文中一共展示了Delaunay.sum方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: create_reachability_graph
# 需要导入模块: from scipy.spatial import Delaunay [as 别名]
# 或者: from scipy.spatial.Delaunay import sum [as 别名]
def create_reachability_graph(self, args):
robot_xml = args.robot_xml
n_data_points = int(args.data_points)
show_graph = args.show_graph
log_file = args.log_file
clip_zero_pts = args.clip_zero_pts
volume_graph = args.volume_graph
from scipy.spatial import ConvexHull
from scipy.spatial import Delaunay
from mpl_toolkits.mplot3d import Axes3D
rospy.loginfo('Loading reachability database for %s' % robot_xml)
# load up the data
ppfile = self.get_filename(robot_xml, args.manipname)
f=h5py.File(ppfile,'r')
reachability3d = f['reachability3d'].value
total_pts = reachability3d.size
nonzero_tot_pts = (reachability3d > 0).sum()
rospy.loginfo('%d out of %d total tested points are reachable (%f%%)' % (nonzero_tot_pts,total_pts,(float(nonzero_tot_pts)/float(total_pts))*100.))
#~ if volume_graph:
#~ from scipy import ndimage #for volume graph
#~ desired_reach = 0.95
#~ volmask = reachability3d >= desired_reach
#~ regions, nregs = ndimage.label(volmask)
#~
#~ fig = plot.figure()
#~ ax = fig.add_subplot(111, projection='3d')
#~ x,y,z = numpy.where(reachability3d >= desired_reach)
#~ every = 2
#~ ax.scatter(x[0::every],y[0::every],z[0::every],c=((0.5,0.5,1,0.8)))
#~
#~ cmap = plot.get_cmap('jet')
#~ for reg in range(1,nregs):
#~ x,y,z = numpy.where(regions == reg)
#~ print "region %s: %s points"%(reg,x.size)
#~ ax.scatter(x[0::every],y[0::every],z[0::every],c=cmap(float(reg)/float(nregs)))
#~
#~ plot.show()
#~ exit()
#orientations range between 0 and 1
#~ orientations = [float(x)/float(n_data_points) + 1/float(n_data_points) for x in range(n_data_points)]
orientations = [float(x)/float(n_data_points) for x in range(n_data_points)]
#omit points with zero reachability (improves graph)
if clip_zero_pts:
orientations[0] += 1/(100*float(n_data_points))
rospy.loginfo('Calculating Reachable Zone Convex Hull')
#get nonzero indices
x,y,z = numpy.where(reachability3d > 0)
nz_points = numpy.array([[x[i],y[i],z[i]] for i in range(len(x))])
convex_hull = ConvexHull(nz_points)
#Plotting! plot the convex hull
#~ fig = plot.figure()
#~ ax = fig.add_subplot(111, projection='3d')
#~ colourmap = []
#~ colours = plot.get_cmap('jet')
#~ for i in range(len(x)):
#~ pt_val = reachability3d[x[i],y[i],z[i]]
#~ col = colours(pt_val/1.2)
#~ colour = col#(col[0],col[1],col[2],pt_val) #vary alpha too
#~ colourmap.append(colour)
#~ every = 5
#~ ax.scatter(x[0::every],y[0::every],z[0::every],c=colourmap[0::every],marker='o')
#~ for simplex in convex_hull.simplices:
#~ plot.plot(x[simplex],y[simplex],z[simplex],'--',c=(1,0,0,1))
#~ plot.show()
#~ #Plotting! plot 2D convex hull
#~ fig = plot.figure()
#~ colourmap = []
#~ colours = plot.get_cmap('jet')
#~ for i in range(len(x)):
#~ if z[i] > 65 and z[i] < 75:
#~ pt_val = reachability3d[x[i],y[i],z[i]]
#~ col = colours(pt_val*5)
#~ plot.plot(y[i],x[i],'o',c=col)
#~ plot.show()
#~ fig = plot.figure()
#~ colourmap = []
#~ colours = plot.get_cmap('jet')
#~ for i in range(len(x)):
#~ if x[i] > 50 and x[i] < 60:
#~ pt_val = reachability3d[x[i],y[i],z[i]]
#~ col = colours(pt_val*5)
#~ plot.plot(y[i],z[i],'o',c=col)
#~ plot.show()
#~ #Plotting! plot whole workspace
#~ fig = plot.figure()
#~ ax = fig.add_subplot(111, projection='3d')
#~ colourmap = []
#.........这里部分代码省略.........